Key advantages for data-driven enterprises
Aresearch study on the use of data by enterprises by 451 Research lists 5 trends that separate enterprises that are more data-driven from the least data-driven. The study lists these trends as:
1. The future of AI will be (more)
automated and explainable.
The shortage of data science skills means that unless machine learning gets easier to implement, progress and adoption will be slow. The long-term goal must be to open up machine learning to all types of developers, not just those with strong data science skills. This also means eventually opening up machine learning to users of l ow-code and no-code development environments.
2. The ‘ last mile’ of data science - operationalization - will be addressed.
Offerings for placing AI and machine learning models into production and handling their ongoing management will burgeon in order to tackle this critical part of data science.
3. DataOps will drive more agile data
To become more datadriven, enterprises need to invest not only in new data processing, analytics and machine learning functionality, but also in more agile approaches to data management that reduce data friction and accelerate time to insight.
4. Hadoop and dat a warehouse
workload convergence will increase.
When Apache Hadoop first appeared on the scene in 2006, it was more a complement than a competitor to existing data warehousing systems. However, distributed data-processing frameworks vendors (initially Hadoop distributors) have changed since then and are coming to market with specific data-warehousing offerings and moving beyond serving as complementary systems to become direct competitors to traditional data warehousing vendors.
5. Industry-specific and cross-industry
enterprise blockchains will go live.
The blockchain crowd is not getting any smaller, but the good news is that more practical uses of the technology are taking off and we are seeing a growing number of industry-specific and crossindustry enterprise blockchain networks going live.
The study maintains that the pace of change will continue to accelerate in 2019 and that these trends are actually influencing each other to drive that change.
WINNERS VS LOSERS
The study elaborates on the winners and losers because of the each of the trends. It says in the case of the first trend, the winners will be those that automate the training of machine learning models; data-driven organizations that understand that large disparate data sets are assets to be embraced and exploited. However, organizations that rely heavily on expensive data science skills or insist on building their own models by hand and vendors that only offer machine learning services via APIs, will stand to lose.
In the case of the second trend, winners will be companies that acknowledge the role of AI and machine learning operationalization in making pervasive intelligence effective and successful and vendors who make machine learning and AI operationalization a core feature of their data science platform, cloud service or data platform. And the losers will be those companies that fail to respond to the importance of operationalization and vendors with a limited view of a data science pipeline.
As regards DataOps and more agile data management, the study says vendors who deliver products and services that are specifically designed to support more agile data management processes and lower time to insight and enterprises that adopt organizational and cultural change to break down barriers between IT and line of business will stand to gain, while vendors that are locked into traditional approaches to data management and enterprises that are too conservative to embrace new approaches to data management and analytics will be the losers.
On the aspect of Hadoop and data warehouse workload convergence increasing, the study feels companies that make better use of their Hadoop systems and those that avoid jumping to conclusions will be the winners, while those that rush to dismiss the distributed data processing systems and organizations that do not fully understand what is required will be the losers.
Pertaining to the fifth aspect of industryspecific and cross-industry enterprise blockchains going live, the study emphasizes that vendors with a hands-on approach who can articulate the capabilities and benefits of their offering and enterprises that are open to new ways of doing business will be the winners, while the losers will be those vendors who develop their offerings in isolation and fail to implement a sustainable business model and enterprises that are too conservative to embrace new and disruptive approaches to doing business.